Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
About this Course
- 5 stars65.28%
- 4 stars25.97%
- 3 stars6.28%
- 2 stars1.57%
- 1 star0.88%
TOP REVIEWS FROM BUILDING BATCH DATA PIPELINES ON GOOGLE CLOUD
very good as a start, needs more practical on some topics like the last ones, and I had a bug with composer lab, but the over all is fine.
Excellent course with appropriate explanation on cloud data fusion, data composer, data proc and cloud data-flow. Must learn course for all aspiring Big Data Engineers.
Good introduction to pipelines building in GCP, Starting labs need to be in more detail. Other than that very good course.
There were some minor problem and mistake in the lab file. The python/java scripts were not explained at all. There are questions about the code itself, but then the questions were not answered.
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